Undergraduate Course: Theory of Statistical Inference (MATH10028)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 10 (Year 4 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | In this course we will develop mathematical aspects of statistical inference. The theory covered provides a greater understanding of the fundamental properties of popular statistical techniques and provides a framework for deriving procedures in more complex situations. |
| Course description |
Topics to be covered include:
1. Parametric families and likelihood.
2. Statistics, Sufficiency and Minimal Sufficiency.
3. Estimation, Unbiasedness, Efficiency, MVUE, Rao--Blackwell Theorem, Cramer--Rao Lower Bound.
4. Hypothesis testing, Neyman--Pearson Lemma.
5. Confidence Intervals, Pivots
6. Decision theory and admissibility of estimators.
7. Shrinkage/James Stein estimators.
8. Selected topics in modern statistics.
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Information for Visiting Students
| Pre-requisites | Visiting students are advised to check that they have studied the material covered in the syllabus of each pre-requisite course before enrolling. |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2022/23, Available to all students (SV1)
|
Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 22,
Seminar/Tutorial Hours 5,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
69 )
|
| Assessment (Further Info) |
Written Exam
95 %,
Coursework
5 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Coursework 5%, Examination 95% |
| Feedback |
Not entered |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S1 (December) | | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Write down formal definitions of statistical properties
- State and prove standard theoretical results in statistical inference
- Construct estimators, hypothesis tests and confidence intervals which satisfy desirable statistical properties
- Apply statistical theorems in examples to ascertain the properties of particular estimators, hypothesis tests and confidence intervals
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Contacts
| Course organiser | Dr Timothy Cannings
Tel:
Email: Timothy.Cannings@ed.ac.uk |
Course secretary | Mrs Alison Fairgrieve
Tel: (0131 6)50 5045
Email: Alison.Fairgrieve@ed.ac.uk |
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